Presentation Abstract: Huge strides have made in the widespread adoption of autonomous and human-in-the-loop cyber-physical systems (CPS), partly fueled by dramatic improvements in learning-based techniques. An important aspect of such CPS applications is that they are safety-critical: any undesirable behavior by such systems can cause serious harm to human lives or property. The formal methods […]
CIS
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Many cryptographic protocols will be rendered insecure if sufficiently powerful quantum computers are built. While this remains at least a few decades away, there is another, more immediate, problem: many widely-used security analysis techniques rely on properties of classical information that do not hold in the quantum setting, rendering the security of many schemes unclear […] |
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ABSTRACT: I'll present research on using large language models (LLMs) to build explainable classifiers. I will show off work from my PhD students and collaborators on several recent research directions: Image classification with explainable features (https://arxiv.org/abs/2211.11158) Text classification with explainable features (work in progress) The importance of faithfulness in explanations (https://arxiv.org/abs/2209.11326) (Time permitting) A […] |
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Today’s hardware cannot keep secrets. Indeed, the past two decades have seen the discovery of a slew of attacks where an adversary exploits hardware features to leak software’s sensitive data. These attacks have shaken the foundations of computer security and caused a major disruption in the software industry. Fortunately, there has been a saving grace, namely the widespread adoption […] |
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Expressive cryptography, including Secure Multi-Party Computation (SMPC) and Fully Homomorphic Encryption (FHE), has the potential to enable transformative new applications, drawing significant interest from industry. Unfortunately, it is often slow and resource-intensive, making those applications difficult to realize. For example, SMPC enables multiple organizations (e.g., hospitals) to run joint computations on their data (e.g., for […] |
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Abstract: Machine learning algorithms are increasingly used in conjunction with optimization to guide decision making. A key challenge is aligning the machine learning loss with the decision-making loss. Existing solutions have limited flexibility and/or scale poorly to large datasets. We propose a principled decision-aware learning algorithm that uses a Taylor expansion of the optimal decision […]
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We will discuss methods of data lookup, with a focus on hash sets / tables, including motivation, properties, and variants. This will be in the context of a "CS 2" or data structures course. We will assume a basic familiarity with programming and comfort with implementing resizable lists; as well as knowledge of (but not […] |
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Humans exhibit a strong tendency to associate with those similar to them. This tendency, termed homophily in the social sciences, impacts both the structure of society and its outcomes. In this talk, Nicole Immorlica discusses the mathematics of homophily. She first quantifies its theoretical implications for geographic segregation. We will see that even tolerant societies […] |
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In the current digital and decentralized world, there is an imminent need for technologies that can provide a fast approach to compute on private data while guaranteeing secrecy. Secure Multiparty Computation (MPC) is one such cryptographic technology that provides an efficient approach to compute on private data. At a high level, MPC is a distributed […] |
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My research focuses on the security, privacy, and transparency of technologies in societal and legal context. My talk will focus on three of my recent works in this space, relating to (1) preventing exploitation of stolen email data, (2) enhancing accountability in electronic surveillance, and (3) legal risks faced by security researchers. |
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Please save the date to join us for this annual distinguished lecture. The Joseph Bordogna Forum will foster conversation and debate regarding important issues at the nexus of technology and society. It will feature lectures and panel discussions on a wide range of contemporary issues that are central to engineering including diversity and inclusion, the […] |
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Technologies that enable confidential communication and anonymous authentication are important for improving privacy for users of internet services. Unfortunately, encryption and anonymity, while good for privacy, make it hard to hold bad actors accountable for misbehavior. Internet services rely on seeing message content to detect spam and other harmful content; services must also be able […] |
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ABSTRACT: Electronic health records (EHRs) offer great promises in advancing clinical research and transforming learning health systems. However, complex, temporal EHRs are fraught with biases and present daunting analytical challenges that, if not addressed, can exacerbate health inequities. EHRs data, recorded at irregular time intervals with varying frequencies, are multi-modal and multi-scale including structured data […] |
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Algorithms make predictions about people constantly. The spread of such prediction systems has raised concerns that machine learning algorithms may exhibit problematic behavior, especially against individuals from marginalized groups. This talk will provide an overview of my research building a theory of "responsible" machine learning. I will highlight a notion of fairness in prediction, called […] |
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